• Journal of Veterinary Clinics
• /
• v.36 no.1
• /
• pp.15-22
• /
• 2019

Highly pathogenic avian influenza (HPAI) is among the top infectious disease priorities in Korea and the leading cause of economic loss in relevant poultry industry. An understanding of the spatial epidemiology of HPAI outbreak is essential in assessing and managing the risk of the infection. Though previous studies have reported the majority of outbreaks occurred clustered in what are preferred to as densely populated poultry regions, especially in southwest coast of Korea, little is known about the spatial distribution of risk areas vulnerable to HPAI occurrence based on geographic information system (GIS). The main aim of the present study was to develop a GIS-based risk index model for defining potential high-risk areas of HPAI outbreaks and to explore spatial distribution in relative risk index for each 252 Si-Gun-Gu (administrative unit) in Korea. The risk index was derived incorporating seven GIS database associated with risk factors of HPAI in a standardized five-score scale. Scale 1 and 5 for each database represent the lowest and the highest risk of HPAI respectively. Our model showed that Jeollabuk-do, Chungcheongnam-do, Jeollanam-do and Chungcheongbuk-do regions will have the highest relative risk from HPAI. Areas with risk index value over 4.0 were Naju, Jeongeup, Anseong, Cheonan, Kochang, Iksan, Kyeongju and Kimje, indicating that Korea is at risk of HPAI introduction. Management and control of HPAI becomes difficult once the virus are established in domestic poultry populations; therefore, early detection and development of nationwide monitoring system through targeted surveillance of high-risk spots are priorities for preventing the future outbreaks.

• Korean Journal of Veterinary Research
• /
• v.49 no.4
• /
• pp.309-317
• /
• 2009

The present study describes an investigation on an epidemic of Tuberculosis (TB) which has been occurred among dairy cattle farms in Jeongeup, Jeollabuk-do since 2007. The investigation was performed in three ways as follows: 1. Collecting information about bovine TB outbreaks using investigation reports, an on-the-spot and tracing-back investigations; 2. Analyzing the outbreak pattern; 3. Establishing hypothesis and performing statistical analysis on potential risk factors. In the early 2000s, TB outbreaks were sporadically reported in beef cattle, and only a small number ($1{\sim}2$) of reactors was confirmed in each of outbreak farms. The number of TB outbreaks has been suddenly increased from 2007, mainly in dairy cattle farms. And these outbreaks were temporarily clustered during the period, from March 2007 to April 2009 (relative risk, RR = 13.7, p < 0.001). And two spatial clusters of which radiuses were 0.3 km (RR = 6.9, p < 0.001) and 0.9 km (RR = 3.6, p < 0.01). The analysis to find risk factors was performed on 99 dairy farms (21 outbreaks), which are located in the most seriously affected village during 2007-2009. Middleman (odds ratio, OR = 47.4, p < 0.05) and raw milk collecting system (OR = 6.9, p < 0.05) were recognized as with the highest association. Considering the fact that all the outbreak farms except one had their own manure composting tank, it might be that the manure containing pathogen was leaked from tank and transmitted to other farms by fomites such as middleman or raw milk collecting system.

• Journal of Korean Society for Atmospheric Environment
• /
• v.25 no.4
• /
• pp.339-346
• /
• 2009

The objectives of this study were to introduce spatial interpolation methods which have been applied in recent papers, to apply three methods (nearest monitor, inverse distance weighting, kriging) to domestic data (Ulsan cohort) as an example of estimating the personal exposure levels. We predicted the personal exposure estimates of 2,102 participants in Ulsan cohort using spatial interpolation methods based on information of their residential address. We found that there was a similar tendency among the estimates of each method. The correlation coefficients between predictions from pairs of interpolation methods (except for the correlation coefficient between nearest montitor and kriging of CO and $SO_2$) were generally high (r=0.84 to 0.96). Even if there are some limitations such as location and density of monitoring station, spatial interpolation methods can reflect spatial aspects of air pollutant and spatial heterogeneity in individual level so that they provide more accurate estimates than monitor data alone. But they may still result in misclassification of exposure. To minimize misclassification for better estimates, we need to consider individual characteristics such as daily activity pattern.

• Journal of Preventive Medicine and Public Health
• /
• v.55 no.2
• /
• pp.164-172
• /
• 2022

Objectives: We aimed to estimate the space-time distribution of the risk of suicide mortality in Iran from 2006 to 2016. Methods: In this repeated cross-sectional study, the age-standardized risk of suicide mortality from 2006 to 2016 was determined. To estimate the cumulative and temporal risk, the Besag, York, and Mollié and Bernardinelli models were used. Results: The relative risk of suicide mortality was greater than 1 in 43.0% of Iran's provinces (posterior probability >0.8; range, 0.46 to 3.93). The spatio-temporal model indicated a high risk of suicide in 36.7% of Iran's provinces. In addition, significant upward temporal trends in suicide risk were observed in the provinces of Tehran, Fars, Kermanshah, and Gilan. A significantly decreasing pattern of risk was observed for men (β, -0.013; 95% credible interval [CrI], -0.010 to -0.007), and a stable pattern of risk was observed for women (β, -0.001; 95% CrI, -0.010 to 0.007). A decreasing pattern of suicide risk was observed for those aged 15-29 years (β, -0.006; 95% CrI, -0.010 to -0.0001) and 30-49 years (β, -0.001; 95% CrI, -0.018 to -0.002). The risk was stable for those aged >50 years. Conclusions: The highest risk of suicide mortality was observed in Iran's northwestern provinces and among Kurdish women. Although a low risk of suicide mortality was observed in the provinces of Tehran, Fars, and Gilan, the risk in these provinces is increasing rapidly compared to other regions.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.19 no.4
• /
• pp.186-198
• /
• 2016

HPAI(Highly Pathogenic Avian Influenza) is a contagious animal disease that spreads rapidly by diffusion after the first occurrence. The disease has brought tremendous social costs and economic losses. KAHIS (Korea Animal Health Information System) is the integrated system for supporting the task of preventing epidemics. They provide decision-support information, recording vehicle visiting times and facility location, etc., which is possible by enforcing registration of all livestock related facilities and vehicles. KAHIS has accumulated spatial and temporal information that enables effective tracing of potential disease trajectories and diffusion through vehicle movements. The contact network is created utilizing spatial and temporal information in KAHIS to inform facility connection via vehicle visitation. Based on the contact network, it is possible to infer spatial and temporal mechanism of disease spread and diffusion. The study objective is to empirically demonstrate how to utilize primary spatial and temporal information in KAHIS in the form of the contact network. Based on the contact network, facilities with the possibility of infection can be pinpointed within the potential spatial and temporal extent where the disease has spread and diffused. This aids the decision-making process in the task of preventing epidemics. By interpreting our demonstration results, policy implications were presented. Finally, some suggestions were made to comprehensively utilize the contact network to draw enhanced decision-support information.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.sup3
• /
• pp.33-37
• /
• 2016

Skin cancer is one of the most common cancers worldwide, including in Iran. Variations in its incidence rate among geographical areas are due to various contributing factors. Since there has been a lack of studies on this topic in our country, the present spatial analysis of skin cancer incidence in Iran in 2009 was conducted using data from the cancer registry system for the country. The reported incidences of the disease were standardized on the basis of the World Health Organization population and the direct method. Then the data were inserted into the GIS software, and finally, using the analysis of hot spots (Getis-Ord Gi), high-risk areas were drawn. Provinces that were 1.9 SD higher or lower than the national average were considered hot spots or cold spots, with significance at the level of 0.05. In 2009, a total of 9,964 cases of skin cancer occurred, 3,696 in women and 6,268 in men (standardized incidence rates of 15.8 and 22.6, respectively). The results of the study showed that in men and women, the disease demonstrated high incidence in the central provinces and desert regions. In women, Yazd Province and in men, Qom Province had significant hot spots (p <0.05). While Isfahan, Markazi, Tehran and Kurdistan provinces were expected to be hot spots, the differences from the national average were not significant at the 0.05 level. As well, the provinces of Sistan Va Baluchistan, Kerman, and Hormozgan were identified as cold or low-risk disease regions (p <0.05). The central provinces of the country due to hot weather conditions, more solar radiation, and closer vicinity to the central desert of Iran demonstrated higher incidence rates for skin cancer, so further epidemiological studies into the etiology and early detection are essential in these areas.

• Environmental Analysis Health and Toxicology
• /
• v.29
• /
• pp.5.1-5.7
• /
• 2014

Objectives Numerous studies have revealed the adverse health effects of acute and chronic exposure to particulate matter less than $10{\mu}m$ in aerodynamic diameter ($PM_{10}$). The aim of the present study was to examine the spatial distribution of $PM_{10}$ concentrations and cardiovascular mortality and to investigate the spatial correlation between $PM_{10}$ and cardiovascular mortality using spatial scan statistic (SaTScan) and a regression model. Methods From 2008 to 2010, the spatial distribution of $PM_{10}$ in the Seoul metropolitan area was examined via kriging. In addition, a group of cardiovascular mortality cases was analyzed using SaTScan-based cluster exploration. Geographically weighted regression (GWR) was applied to investigate the correlation between $PM_{10}$ concentrations and cardiovascular mortality. Results An examination of the regional distribution of the cardiovascular mortality was higher in provincial districts (gu) belonging to Incheon and the northern part of Gyeonggi-do than in other regions. In a comparison of $PM_{10}$ concentrations and mortality cluster (MC) regions, all those belonging to MC 1 and MC 2 were found to belong to particulate matter (PM) 1 and PM 2 with high concentrations of air pollutants. In addition, the GWR showed that $PM_{10}$ has a statistically significant relation to cardiovascular mortality. Conclusions To investigate the relation between air pollution and health impact, spatial analyses can be utilized based on kriging, cluster exploration, and GWR for a more systematic and quantitative analysis. It has been proven that cardiovascular mortality is spatially related to the concentration of $PM_{10}$.

• The Korean Journal of Applied Statistics
• /
• v.23 no.2
• /
• pp.335-344
• /
• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Genomics & Informatics
• /
• v.2 no.2
• /
• pp.92-98
• /
• 2004

A cDNA microarray experiment is one of the most useful high-throughput experiments in medical informatics for monitoring gene expression levels. Statistical analysis with a cDNA microarray medical data requires a normalization procedure to reduce the systematic errors that are impossible to control by the experimental conditions. Despite the variety of normalization methods, this. paper suggests a more general and synthetic normalization algorithm with a control gene set based on previous studies of normalization. Iterative normalization method was used to select and include a new control gene set among the whole genes iteratively at every step of the normalization calculation initiated with the housekeeping genes. The objective of this iterative normalization was to maintain the pattern of the original data and to keep the gene expression levels stable. Spatial plots, M&A (ratio and average values of the intensity) plots and box plots showed a convergence to zero of the mean across all genes graphically after applying our iterative normalization. The practicability of the algorithm was demonstrated by applying our method to the data for the human photo aging study.

• Journal of Preventive Medicine and Public Health
• /
• v.40 no.3
• /
• pp.233-238
• /
• 2007

Objectives : We aimed to assess the relationship between long-term exposure to air pollution and lung cancer in the Republic of Korea. Methods : Using the Annual Report of Ambient Air Quality in Korea, Annual Report of National Cancer Registration, and Annual Report on the Cause of Death Statistics, we calculated the standardized mortality ratio (SMR) and standardized incidence ratio (SIR) of lung cancer for both sexes in 74 areas from 7 Korean metropolitan cities. We performed random intercept, Poisson regression using empirical Bayes method. Results : Both SMRs and SIRs in the 7 metropolitan cities were higher in women than in men. Mean SIRs were 99.0 for males and 107.0 for females. The association between $PM_{10}$ and lung cancer risk differed according to gender. $PM_{10}$ was not associated with the risk of lung cancer in males, but both incidence and mortality of lung cancer were positively associated with $PM_{10}$ in females. The estimated percentage increases in the rate of female lung cancer mortality and incidence were 27% and 65% at the highest $PM_{10}$ category $({\geq}70\;{\mu}g/m^3)$, compared to the referent category $({\geq}50\;{\mu}g/m^3)$. Conclusions : Long-term exposure to $PM_{10}$ was significantly associated with female lung cancer incidence in 7 Korean metropolitan cities. Further study is undergoing to estimate the relative risk of $PM_{10}$ using multi-level analysis for controlling individual and regional confounders such as smoking and socioeconomic position.